In the field of application servers and distributed systems, clusters of servers are often used to provide highly available and scalable resources. One example of an application server is the WebLogic Server from BEA Systems, Inc. A cluster (such as a WebLogic Server cluster) comprises multiple server instances running simultaneously and working together to provide increased scalability and reliability. A cluster appears to clients to be a single server. The server instances that constitute a cluster can run on the same machine, or be located on different machines. A cluster's capacity can be increased by adding additional server instances to the cluster on an existing machine, or by adding machines to the cluster to host the incremental server instances. Each server instance in a cluster must typically run the same version of the server product.
In terms of how a cluster relates to the environment in which the application server exists, a cluster is usually part of a particular server (e.g. WebLogic Server) domain. A domain is an interrelated set of resources that are managed as a unit. A domain includes one or more server instances, which can be clustered, non-clustered, or a combination of clustered and non-clustered instances. A domain can include multiple clusters. A domain also contains the application components deployed in the domain, and the resources and services required by those application components and the server instances in the domain. Examples of the resources and services used by applications and server instances include machine definitions, optional network channels, connectors, startup classes, EJB's, JSPs, etc. An administrator can use a variety of criteria for organizing server instances into domains. For instance, they might choose to allocate resources to multiple domains based on logical divisions of the hosted application, geographical considerations, or the number or complexity of the resources under management.
In a WebLogic domain, one WebLogic Server instance typically acts as the Administration Server—the server instance which configures, manages, and monitors all other server instances and resources in the domain. If a domain contains multiple clusters, each server in the domain has the same Administration Server.
Clustered server instances behave similarly to non-clustered instances, except that they provide failover and load balancing. The process and tools used to configure clustered server instances are the same as those used to configure non-clustered instances. A server cluster provides the following benefits and features:                Scalability—The capacity of an application deployed to a cluster can be increased dynamically to meet demand. Server instances can be added to a cluster without interruption of service—the application continues to run without impact to clients and end users.        High-Availability—In a cluster, application processing can continue when a server instance fails. Application components are “clustered” by deploying them on multiple server instances in the cluster—so, if a server instance on which a component is running fails, another server instance on which that component is deployed can continue application processing.        Failover—Failover means that when an application component (typically referred to as an “service” in the following sections) doing a particular “job”—some set of processing tasks—becomes unavailable for any reason, a copy of the failed service finishes the job. For the new service to be able to take over for the failed service there must be a copy of the failed service available to take over the job. There must also be information, available to other services and the program that manages failover, defining the location and operational status of all services—so that it can be determined that the first service failed before finishing its job. There must also be information, available to other services and the program that manages failover, about the progress of jobs in process—so that a service taking over an interrupted job knows how much of the job was completed before the first service failed, for example, what data has been changed, and what steps in the process were completed. Many application servers, including WebLogic Server, use standards-based communication techniques and facilities—multicast, IP sockets, and the Java Naming and Directory Interface (JNDI)—to share and maintain information about the availability of services in a cluster. These techniques allow the server to determine that a service stopped before finishing its job, and where there is a copy of the service to complete the job that was interrupted. Information about what has been done on a job is called state. WebLogic Server maintains information about state using techniques called session replication and replica-aware stubs. When a particular service unexpectedly stops doing its job, replication techniques enable a copy of the service pick up where the failed service stopped, and finish the job.        Load Balancing—Load balancing is the even distribution of jobs and associated communications across the computing and networking resources in the application server environment. For load balancing to occur there must be multiple copies of a service that can do a particular job. Information about the location and operational status of all services must also be available. In addition, WebLogic Server allows services to be clustered—deployed on multiple server instances—so that there are alternative services to do the same job. WebLogic Server shares and maintains the availability and location of deployed services using multicast, IP sockets, and JNDI.        
Cluster members must typically keep in touch with one another to ensure consistency throughout the cluster. This is particularly relevant in keeping track of the various resources, provided by the cluster, including the fact that some resources may be provided by certain cluster members, while other cluster members provide a different set of resources, services, etc. Many application server cluster products, including for example BEA's WebLogic server product maintain a cluster-wide JNDI tree or naming service that keeps track of all of the available resources and services in the cluster. Each cluster member in the cluster maintains its own naming service whose view mimics that of the global tree. In this manner, when a client (or server, or any other process) accesses a server in the cluster they get the same set of available resources, which attempts to provide consistency throughout the cluster. During normal use each server within the cluster binds its resources to its internal naming service, which is then replicated (advertised) to all of the other cluster members. For example, if a server A is providing a particular service, then information about this server is first bound to server A's naming service (for example its JNDI tree), and from there is replicated to the other servers.
Typically, the approach used to replicate information from one cluster member or server to another server within the cluster is to multicast the information. Using multicast, information about all of a servers resources, services, etc. is multicast to each other member of the cluster. However, mutlicast is an unreliable transport mechanism. The packet of information could be intercepted or dropped along the way, resulting in one server having a different view of the naming service from the view at another server. As such, this impinges on the consistency throughout the cluster.
Traditionally, there are two primary methods to make the multicast process more reliable at a higher level. A first approach is for the second (receiving) server to issue a request (for example a NAK request) to the first (sending) server, saying “I missed an update packet—please resend it”. In return the second server will be sent the missing update. Another approach is for the first server to send an aggregated view (a statedump) of all of its resources and services to the second server. The statedump describes the aggregate view of the services provided by a server. Large packets of multicast messages exchanged between servers in a cluster can potentially destabilize the cluster. Frequent resend requests for service advertisements can quickly overflow the operating system message buffers, causing stability problems. As the number of services provided by a server increase, so does the size of the statedump. Coupled with the increasing of a cluster, this could lead to longer startup time and the time each server takes to stabilize in a cluster. The need to send frequent large multicast messages also impacts the cluster scalability and the performance.